Measures used to assess and compare the quality of health care organizations are classified as either a structure, process, or outcome measure. Known as the Donabedian model, this classification system was named after the physician and researcher who formulated it.
Structural Measures
Structural measures give consumers a sense of a health care provider’s capacity, systems, and processes to provide high-quality care. For example:
- Whether the health care organization uses electronic medical records or medication order entry systems.
- The number or proportion of board-certified physicians.
- The ratio of providers to patients.
Process Measures
Process measures indicate what a provider does to maintain or improve health, either for healthy people or for those diagnosed with a health care condition. These measures typically reflect generally accepted recommendations for clinical practice. For example:
- The percentage of people receiving preventive services (such as mammograms or immunizations).
- The percentage of people with diabetes who had their blood sugar tested and controlled.
Process measures can inform consumers about medical care they may expect to receive for a given condition or disease, and can contribute toward improving health outcomes. The majority of health care quality measures used for public reporting are process measures.
Outcome Measures
Outcome measures reflect the impact of the health care service or intervention on the health status of patients. For example:
- The percentage of patients who died as a result of surgery (surgical mortality rates).
- The rate of surgical complications or hospital-acquired infections.
Outcome measures may seem to represent the “gold standard” in measuring quality, but an outcome is the result of numerous factors, many beyond providers’ control. Risk-adjustment methods—mathematical models that correct for differing characteristics within a population, such as patient health status—can help account for these factors. However, the science of risk adjustment is still evolving. Experts acknowledge that better risk-adjustment methods are needed to minimize the reporting of misleading or even inaccurate information about health care quality.
